Machine learning-assisted design of a dendritic cell nanovaccine inducing twin immunity against monkeypox

The global emergence of monkeypox virus (MPXV) has created an urgent need for effective vaccines that induce robust immune responses. Here, we report a biomimetic nano-vaccine platform based on engineered dendritic cell membrane vesicles displaying M1R (M1R-CMVs), designed via genetic engineering with machine learning-assisted preliminary screening of physicochemical parameters including particle size (~190 nm) and zeta potential (-18 mV). Subcutaneous delivery of M1R-CMVs with CpG adjuvant induced high titers of M1R-specific IgG and potent neutralizing antibodies. The vaccine promoted broad T cell activation, characterized by enhanced CD4⁺ and CD8⁺ T cell responses in spleen and lymph nodes, and established durable T cell memory. In vitro studies demonstrated that M1R-CMVs enhance dendritic cell maturation and T cell proliferation. Prime-boost immunization further amplified both humoral and cellular immunity, with significant increases in neutralizing antibody titers and effector T cell populations. Furthermore, the vaccine exhibited a favorable safety profile in vivo with no significant toxicity observed. Our findings demonstrate a biomimetic vaccine design strategy integrating engineered vesicles with machine learning-assisted physicochemical analysis, providing a promising approach to combat monkeypox.